Main questions

• How did you play differently in different versions?
• What in real life is similar to each version of the game?
• How did you decide whether or not to help others?
• What does this have to do with social networks and social capital?!

Debrief

• What did you think about while playing?
• How did you feel as you played? Did those feeling change across different versions of the game?
• When do you help others in real life?

Debrief

• Were resources and abilities distributed fairly?
• How should resources be distributed in the real world?
• What role did communication play? How did your group make decisions?
• Did you work to make things equal? Why or why not?
• What kinds of inequality appeared in the game?

Debrief

• Did anyone sanction someone else? Why?
• How did others respond to being sanctioned?
• What is similar to a “sanction” in the real world?

Aspects of visualizations

• Nodes
• Edges
• Location

Nodes

• Information can be conveyed by:
  • Shape, size, color
• Shape
  • Typically categorical (e.g., gender, age range)
• Size
  • Often a network measure, but can be something about node
• Color
  • Often community detection

Examples

With node shapes

Nodes sized by betweenness centrality

Nodes colored by community

Edges

• Size
  • Typically represent weight of relationship
• Color
  • Typically represents different types of relationships

Examples

Edge width as weight

Edge color as type

Position

• Can represent literal distance
  • Cities
  • Seating chart
• Or social distance
  • Formal hierarchy
  • Degree centrality

Node placement can make a big difference in how a network is perceived

Today’s activity

• Start working on DataCamp Network Analysis, chapters 2 and 3

Today’s Dad Joke

Within minutes, the detective knew exactly what the murder weapon was.

It was a brief case.

Housekeeping

• Self-assessment overview
  • R
  • Coming with questions / Office hours
  • Readings
    • Too long
    • Put on Brightspace
  • Posting slides
• In class
  • Break
  • Dealing with confusion
    • More group discussion
    • Questions in class
    • Writing on projector vs. on board?

DataCamp Review

• neighbors()
• ego()
• make_ego_network()
• Come back to:
  • lapply
  • randomization
  • transitivity
  • cliques

What makes for a good network visualization?

Kozo Sugiyama’s rules:

1. Lines should be straight.
2. Lines should be far apart from one another.
3. Lines should not cross or touch.
4. Lines should be easy to follow from one node to another.
5. Nodes that connect should be close.
6. Nodes that are most central should be close to the center of the graph.
7. Nodes that are similar in some way should be placed near one another.

Activity

Find and Assess a network visualization

• Use Google Images (or similar) to find an image of a network graphs.
• What do you think the image does well and poorly? Does it follow Sugiyama’s rules?
• Put the image (and your assessment) on the padlet at https://padlet.com/jdfoote1/networks (link is also on wiki)

Discussion

• Did you agree with Sugiyama’s rules?
• What types of color/shape/size approaches were effective?

Visualization Competition

• Dutch school dataset (on wiki)
• In groups of 2-3
  • Come up with question
  • Come up with visualization approach
• We will work on this more next Thursday

Homework

• Scott Feld guest lecture
  • Summary and questions assignment